Fake News API

Author: vishakraj25

fakenewsgenerator.py

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+import feedparser
+import itertools
+import requests
+import schedule
+#import re
+import schedule
+import time
+
+
+try:
+    from bs4 import BeautifulSoup
+except ImportError:
+    from BeautifulSoup import BeautifulSoup
+import pandas as pd
+
+
+# Function to fetch the rss feed and return the parsed RSS
+def parseRSS( rss_url ):
+        return feedparser.parse( rss_url ) 
+
+    # Function grabs the rss feed headlines (titles) and returns them as a list
+def get( rss_url ):
+        all_links=[]
+        all_category=[]
+        feed = parseRSS( rss_url )
+        for newsitem in feed['items']:
+            all_links.append(newsitem['link'])
+            all_category.append(newsitem['title'])
+        return(all_links, all_category)
+
+def fakenewsgenerator():
+
+    all_labels=[]
+
+    # Iterate over the feed urls
+    all_links, all_category = get('http://www.fakingnews.com/feed')
+    print(all_links)
+    content=[]
+    for x in all_links:
+        r = requests.get(x,verify=False)
+        soup = BeautifulSoup(r.content, 'lxml')
+        print(x)
+        body=[]
+        try:
+            for i in soup.findAll("div", {"class": "article-content"}):
+                if(i.get_text()) not in ['','\xa0']:
+                    body.append(i.get_text())
+
+        except:
+                continue
+
+        
+        body= ''.join(body)
+        content.append(body)
+        print(body)
+
+    for a in range(len(all_category)):
+        all_labels.append("FAKE")
+
+
+    list_of_tuples = list(zip(all_links, content, all_category, all_labels))  
+    df = pd.DataFrame(list_of_tuples, columns=['all_links','text','title','label'])
+    df.to_excel("fakenewsgenerator.xlsx",index=False)
+
+    
+fakenewsgenerator()